
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))


# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "54"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder


# Use environment variables to figure out path to the csvs and auto_metrics
antenna = os.environ["ANTENNA"]
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')

antenna = "111"
csv_folder = "/home/obs/src/H5C_Notebooks/_rtp_summary_"
auto_metrics_folder = "/home/obs/src/H5C_Notebooks/auto_metrics_inspect"


display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))


import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna


# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, '*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')

Found 75 csvs in /home/obs/src/H5C_Notebooks/_rtp_summary_
Found 71 auto_metrics notebooks in /home/obs/src/H5C_Notebooks/auto_metrics_inspect


# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0

def jd_to_summary_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H5C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'

def jd_to_auto_metrics_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H5C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'


this_antenna = None
jds = []

# parse information about antennas and nodes
for csv in csvs:
    df = pd.read_csv(csv)
    for n in range(len(df)):
        # Add this day to the antenna
        row = df.loc[n]
        antnum = row['Ant']
        if antnum != int(antenna):
            continue
            
        if this_antenna is None:
            this_antenna = Antenna(row['Ant'], row['Node'])
        jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
        jds.append(jd)
        this_antenna.add_day(jd, row)
        break


# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]

df = pd.DataFrame(to_show)

# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
    df[col] = bar_cols[col]

z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
    df[col] = z_score_cols[col]

ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
    df[col] = ant_metrics_cols[col]

redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]   
for col in redcal_cols:
    df[col] = redcal_cols[col]

# style dataframe
table = df.style.hide_index()\
          .applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
          .background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
          .background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
          .applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
          .format({col: '{:,.4f}'.format for col in z_score_cols}) \
          .format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
          .format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
          .set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])


display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))


html_to_display = ''
for am_html in auto_metric_htmls:
    # read html into a list of lines
    with open(am_html) as f:
        lines = f.readlines()
    
    # find section with this antenna's metric plots and add to html_to_display
    jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
    try:
        section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
    except ValueError:
        continue
    html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
    for line in lines[section_start_line + 1:]:
        html_to_display += line
        if '<hr' in line: 
            break


HTML(html_to_display)

JDs	A Priori Status	Auto Metrics Flags	Dead Fraction in Ant Metrics (Jee)	Dead Fraction in Ant Metrics (Jnn)	Crossed Fraction in Ant Metrics	Flag Fraction Before Redcal	Flagged By Redcal chi^2 Fraction	ee Shape Modified Z-Score	nn Shape Modified Z-Score	ee Power Modified Z-Score	nn Power Modified Z-Score	ee Temporal Variability Modified Z-Score	nn Temporal Variability Modified Z-Score	ee Temporal Discontinuties Modified Z-Score	nn Temporal Discontinuties Modified Z-Score	Average Dead Ant Metric (Jee)	Average Dead Ant Metric (Jnn)	Average Crossed Ant Metric	Median chi^2 Per Antenna (Jee)	Median chi^2 Per Antenna (Jnn)
2459594	digital_ok	0.00%	0.00%	0.00%	0.00%	1.08%	0.00%	1.030239	-0.798504	0.488087	-0.674357	-0.005000	0.191149	0.594438	-0.822183	0.7433	0.7696	0.2702	3.495076	3.185999
2459593	digital_ok	0.00%	0.00%	0.00%	0.00%	2.15%	0.00%	0.132891	0.007810	0.375090	-0.615650	0.920062	2.124663	0.772172	1.203979	0.6729	0.6692	0.2560	2.170339	2.279452
2459592	digital_ok	0.00%	100.00%	100.00%	0.00%	-	-	0.225538	-0.831199	-0.286897	-1.043373	0.874643	2.628865	1.806705	0.005166	0.0302	0.0548	0.0029	nan	nan
2459591	digital_ok	0.00%	0.00%	0.00%	0.00%	1.62%	2.16%	-0.059679	0.551087	0.397884	-0.233437	-0.543929	0.769960	3.527943	1.500173	0.6098	0.6196	0.3577	1.702141	1.673630
2459590	digital_ok	0.00%	0.00%	0.00%	0.00%	1.62%	0.00%	0.117183	0.683928	-0.023469	-0.595132	-1.249067	0.768934	3.323477	1.687596	0.6176	0.6243	0.3511	2.023269	2.035366
2459589	digital_ok	0.00%	0.00%	0.00%	0.00%	2.69%	0.00%	0.043174	0.280614	-0.688361	-0.647800	-1.118459	0.343516	-0.059712	0.030487	0.6572	0.6556	0.2895	1.999076	1.868572
2459588	digital_ok	0.00%	0.00%	0.00%	0.00%	2.69%	0.00%	0.750703	-0.433652	0.812878	-0.900037	-0.354473	0.939214	1.089788	-0.079955	0.7051	0.6926	0.2396	2.903346	2.434982
2459587	digital_ok	100.00%	-	-	-	100.00%	0.00%	0.161072	0.848468	1.443546	0.135349	0.789045	0.434838	7.023342	4.361103	nan	nan	nan	14.299915	17.507083
2459586	digital_ok	0.00%	0.00%	0.00%	0.00%	3.24%	0.00%	-0.369891	-0.146913	-0.812807	0.332237	-0.756963	-0.541813	2.808959	0.198325	0.6200	0.6290	0.3372	1.619291	1.600536
2459585	digital_ok	0.00%	100.00%	100.00%	0.00%	100.00%	0.00%	-0.394059	0.456597	-0.461865	0.040009	-0.442059	0.963539	3.013730	1.225868	0.0333	0.0535	0.0035	0.000000	0.000000
2459584	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.086572	0.487141	-0.968600	-0.928986	0.419995	0.216222	4.813507	0.483494	0.5671	0.5774	0.3492	8.179404	8.319624
2459583	digital_ok	0.00%	0.00%	0.00%	0.00%	3.23%	0.00%	-0.294735	0.133781	-0.910014	-0.902286	-0.035935	0.395245	3.783255	0.227907	0.6218	0.6326	0.3694	1.705483	1.764049
2459582	digital_ok	0.00%	0.00%	0.00%	0.00%	2.70%	0.00%	-0.463642	0.077516	-0.718251	-0.749065	-0.674305	0.541269	1.088377	-0.393594	0.6282	0.6367	0.3703	1.733832	1.771036
2459581	digital_ok	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459580	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.087941	0.220063	-0.770064	-0.746155	-0.059836	0.530015	6.957278	1.047005	0.6327	0.6410	0.3685	4.969878	4.764771
2459579	digital_ok	0.00%	0.00%	0.00%	0.00%	3.76%	0.00%	-0.289787	-0.019441	-0.752754	-0.752327	-0.708867	0.302398	-0.296876	-0.431434	0.6293	0.6376	0.3729	1.891358	1.837719
2459578	digital_ok	100.00%	100.00%	100.00%	0.00%	-	-	-0.494626	-0.049302	-0.879123	-0.379944	-0.523964	5.704517	1.248087	-0.291814	0.0311	0.0550	0.0026	nan	nan
2459577	digital_ok	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459576	digital_ok	0.00%	0.00%	0.00%	0.00%	4.30%	0.00%	-0.082913	0.497685	-0.345945	-0.674720	-0.664990	0.702421	0.035853	1.789451	0.6508	0.6612	0.3708	1.582095	1.698300
2459575	digital_ok	0.00%	0.00%	0.00%	0.00%	5.91%	6.45%	0.291683	-0.174148	-0.812285	-0.819593	-0.914272	-0.220865	-0.812640	-0.727637	0.7213	0.7240	0.3200	1.656265	1.734988
2459574	digital_ok	0.00%	0.00%	0.00%	0.00%	3.78%	0.00%	0.051669	0.683704	-0.691430	-0.874946	-0.193861	1.189886	0.492875	1.660536	0.6486	0.6576	0.3720	1.551921	1.648025
2459573	digital_ok	0.00%	0.00%	0.00%	0.00%	3.78%	0.54%	0.206462	-0.003790	-0.812884	-0.797101	-0.860120	0.819807	1.001198	0.429857	0.6447	0.6551	0.3746	1.648334	1.651773
2459572	digital_ok	0.00%	0.00%	0.00%	0.00%	3.78%	0.00%	-0.228370	-0.130944	-0.639285	-0.808842	-0.937967	0.378021	-0.283682	0.018678	0.6452	0.6548	0.3756	1.409257	1.487602
2459571	digital_ok	100.00%	100.00%	100.00%	0.00%	-	-	-0.331945	-0.002286	-0.886867	-0.487344	0.343369	4.927018	1.918848	0.572947	0.0285	0.0435	0.0028	nan	nan
2459570	digital_ok	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459569	digital_ok	0.00%	0.00%	0.00%	0.00%	4.32%	0.54%	0.113426	0.551061	-0.733166	-0.865054	-0.644803	-0.323725	-0.645666	-0.693113	0.7292	0.7350	0.2366	2.388378	2.243753
2459566	digital_ok	0.00%	0.00%	0.00%	0.00%	4.32%	0.00%	0.037616	2.052525	-0.771687	-0.687515	-0.964476	0.004281	1.729165	2.674174	0.6435	0.6481	0.3784	1.726373	1.785017
2459565	digital_ok	0.00%	-	-	-	93.33%	0.00%	1.518751	1.518751	1.412081	1.412081	0.654293	0.654293	0.137774	0.137774	nan	nan	nan	0.000000	0.000000
2459564	digital_ok	0.00%	0.00%	0.00%	0.00%	5.20%	0.00%	-0.347584	0.786402	-0.375490	-0.683745	-0.041339	0.010991	2.886871	0.935144	0.6469	0.6482	0.3828	1.677714	1.610273
2459563	digital_ok	0.00%	0.00%	0.00%	0.00%	5.38%	0.00%	-0.101269	1.129734	-0.813355	-0.668473	-0.969156	0.323007	-0.519430	-0.313475	0.6484	0.6522	0.3732	1.625158	1.754690
2459562	digital_ok	0.00%	0.00%	0.00%	0.00%	4.86%	0.00%	-0.340689	0.426075	-0.091526	-0.242299	0.267303	0.248510	-0.053457	-0.022559	0.6483	0.6549	0.3761	1.767222	1.716891
2459561	digital_ok	0.00%	0.00%	0.00%	0.00%	4.86%	0.00%	-0.402854	0.713114	-0.335164	-0.352024	-0.274052	0.215830	-0.076862	0.588002	0.6545	0.6642	0.3734	1.593219	1.672824
2459560	digital_ok	0.00%	0.00%	0.00%	0.00%	4.86%	0.00%	-0.257684	0.540380	-0.095223	-0.356365	-0.228249	0.386169	0.594689	0.782915	0.6509	0.6546	0.3788	1.691774	1.673070
2459559	digital_ok	0.00%	0.00%	0.00%	0.00%	5.38%	0.00%	-0.445216	0.592406	-0.244595	-0.418835	-0.268273	0.291277	0.212196	0.508845	0.6509	0.6564	0.3675	1.608169	1.616858
2459558	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.070358	1.193353	-0.617708	-0.714731	0.058136	0.627967	4.448566	2.273695	0.6554	0.6590	0.3750	4.148724	4.125412
2459557	digital_ok	-	100.00%	100.00%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.0356	0.0510	0.0057	nan	nan
2459556	digital_ok	0.00%	0.00%	0.00%	0.00%	4.86%	0.00%	-0.221732	1.188479	-0.844112	-0.763230	-1.176816	0.603114	-0.639337	1.404973	0.6467	0.6525	0.3767	1.563265	1.618217
2459554	digital_ok	-	0.00%	0.00%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.6553	0.6597	0.3844	nan	nan
2459553	digital_ok	-	0.00%	0.00%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.6531	0.6583	0.3820	nan	nan
2459552	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.657019	10.850221	-0.865695	-0.054107	-0.850044	1.805579	0.167068	1.341175	0.6578	0.6467	0.3774	4.830095	4.802019
2459551	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.385923	5.054793	-0.187730	-0.519611	0.037715	-0.517392	0.572793	1.467035	0.6459	0.6365	0.3765	4.229894	3.517508
2459550	digital_ok	-	100.00%	100.00%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.0307	0.0458	0.0033	nan	nan
2459549	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.246240	8.175138	-0.894784	-0.331279	-0.569175	1.284080	4.417077	2.659340	0.6503	0.6438	0.3844	3.681620	3.394282
2459542	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.070353	9.883434	-0.601544	0.173976	-0.405813	-0.132790	0.984609	1.704581	0.7195	0.7092	0.3442	3.930310	3.479072
2459541	digital_ok	100.00%	1.34%	1.34%	0.00%	100.00%	0.00%	0.397770	9.469768	-1.048516	-0.346876	-0.775562	1.399138	0.645701	0.341487	0.7105	0.6985	0.3234	5.017814	4.286880
2459540	digital_ok	0.00%	0.00%	0.00%	0.00%	21.88%	0.00%	-0.098451	-0.547158	-0.503740	-0.301694	1.171379	-0.569108	1.561610	0.445364	0.7181	0.7175	0.3355	1.537411	1.534650
2459536	digital_ok	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	0.407314	-0.181707	-0.452669	-0.465524	-0.141890	6.312693	11.912176	1.713993	0.0606	0.0704	0.0076	0.000000	0.000000
2459535	digital_ok	0.00%	100.00%	100.00%	0.00%	100.00%	0.00%	-0.227648	-0.731946	-0.307094	-0.299048	1.067822	-0.101874	1.959425	0.457328	0.0772	0.0649	0.0089	1.325137	1.325662
2459534	digital_ok	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	-0.280333	-1.021580	-0.390243	-0.324343	1.459497	0.536323	4.907429	1.039300	0.0682	0.0633	0.0073	4.074878	4.282532
2459533	digital_ok	0.00%	100.00%	100.00%	0.00%	100.00%	0.00%	-0.114057	-0.409082	-0.767816	-0.703400	-0.292010	0.826701	0.296086	0.134371	0.0626	0.0655	0.0075	16.753272	18.522879
2459532	digital_ok	0.00%	100.00%	100.00%	0.00%	100.00%	0.00%	-0.147092	-0.265940	-0.882196	-0.897239	0.040614	0.284105	2.203901	0.046763	0.0602	0.0606	0.0062	16.909080	17.955740
2459530	digital_ok	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	-0.531498	0.097147	-0.204184	-0.343169	-0.163018	0.836398	4.356072	5.818512	0.0671	0.0673	0.0078	0.000000	0.000000
2459527	digital_ok	0.00%	-	-	-	100.00%	0.00%	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459524	digital_ok	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.016798	1.400342	-0.636545	-0.836396	-0.846560	2.502797	0.188922	0.923657	0.9115	0.9378	0.2968	0.000000	0.000000
2459523	digital_ok	100.00%	-	-	-	100.00%	0.00%	-0.012046	4.979153	-0.563185	-0.625905	1.974529	2.639024	2.105321	2.551361	nan	nan	nan	13.150715	13.109267
2459522	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.334033	3.576851	-0.958689	-0.666865	0.550082	1.613934	12.473738	1.914591	0.6280	0.6936	0.3927	0.000000	0.000000
2459513	digital_ok	100.00%	100.00%	100.00%	0.00%	-	-	-0.201714	-0.021659	-0.832405	-0.843886	0.273817	10.824975	5.764568	1.745869	0.0433	0.0472	0.0062	nan	nan
2459508	digital_ok	0.00%	0.00%	0.00%	0.00%	81.58%	0.00%	-0.203186	-0.366408	-0.834595	-1.045321	-0.738589	1.161945	-0.573253	-0.717585	0.9069	0.9536	0.1880	0.000000	0.000000
2459505	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.072639	-0.323184	-0.842493	-0.786752	-0.278178	7.130197	15.130453	6.299730	0.8856	0.8648	0.1974	14.708673	18.056835
2459503	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.087135	-0.571423	-0.875453	-0.903513	0.271118	1.538567	7.233667	4.259357	0.8652	0.8594	0.4393	0.000000	0.000000
2459501	digital_ok	0.00%	0.00%	0.00%	0.00%	76.74%	0.00%	-0.207997	0.199750	-0.147310	-0.682272	-0.400873	-0.291778	2.425849	2.723580	0.8675	0.9036	0.3563	0.000000	0.000000
2459500	digital_ok	0.00%	0.00%	0.00%	0.00%	94.74%	0.00%	0.493060	-0.558249	0.234236	-1.265195	2.345962	0.566840	3.462716	1.315118	0.8718	0.8983	0.3477	0.000000	0.000000
2459499	digital_ok	0.00%	0.00%	0.00%	0.00%	97.37%	0.00%	-0.349310	-0.394726	-0.712829	-1.304213	0.318045	-0.035294	0.130676	1.149152	0.8942	0.9404	0.1611	0.000000	0.000000
2459498	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.365529	-0.516323	-0.605846	-0.904898	0.316919	1.285156	0.009038	6.570974	0.8834	0.9000	0.3749	0.000000	0.000000
2459497	digital_ok	0.00%	0.00%	0.00%	0.00%	97.37%	0.00%	-0.564519	-0.263881	-0.660112	-0.667569	0.306732	0.372829	3.448443	-0.161737	0.8966	0.9323	0.3009	0.000000	0.000000
2459496	digital_ok	0.00%	0.00%	0.00%	0.00%	94.74%	0.00%	-0.590001	-0.643852	-0.726381	-0.848856	0.342143	0.449419	3.257925	2.742722	0.9098	0.9155	0.3528	0.000000	0.000000
2459495	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.472996	-0.349877	-0.809918	-0.653967	0.614290	0.921580	4.327056	4.963132	0.9045	0.9111	0.3882	0.000000	0.000000
2459494	digital_ok	0.00%	0.00%	0.00%	0.00%	94.74%	0.00%	-0.595547	-0.491904	-0.484581	-0.921576	1.049362	0.834880	-0.782529	1.641059	0.8946	0.9028	0.3992	0.000000	0.000000
2459492	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.741812	0.764757	-1.329543	-0.302579	-1.498275	4.107407	-0.068678	9.160159	0.7600	0.8149	0.3182	7.653890	6.671247
2459491	digital_ok	0.00%	0.00%	0.00%	0.00%	50.00%	0.00%	0.697574	0.543775	-1.409529	-0.640675	-0.771987	0.743444	1.768027	1.668492	0.7992	0.8266	0.2672	0.728595	0.674039
2459490	digital_ok	0.00%	0.00%	0.00%	0.00%	47.37%	0.00%	-0.022305	0.876384	-1.916131	-0.378699	-1.117740	2.218552	0.616841	1.532236	0.7508	0.8106	0.3647	1.484569	1.408502
2459489	digital_ok	0.00%	0.00%	0.00%	0.00%	47.37%	0.00%	0.827794	1.256907	-1.582486	-0.557545	-0.918544	2.894831	0.921070	1.541893	0.7694	0.8158	0.3219	1.636780	1.594677
2459488	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	1.091359	0.769959	-1.151308	-0.441924	-1.319977	2.880291	0.452902	7.733965	0.7667	0.8186	0.3423	0.000000	0.000000

Antenna Season Report Notebook¶

Antenna 111 Report

Load relevant info from summary CSVs¶

Table 1: Per-Night RTP Summary Info For This Atenna¶

Antenna 111, Node 10:

Load antenna metric spectra and waterfalls from auto_metrics notebooks.¶

Figure 1: Antenna autocorrelation metric spectra and waterfalls.¶

Antenna 111: 2459595

Antenna 111: 2459594

Antenna 111: 2459593

Antenna 111: 2459592

Antenna 111: 2459591

Antenna 111: 2459590

Antenna 111: 2459589

Antenna 111: 2459588

Antenna 111: 2459587

Antenna 111: 2459586

Antenna 111: 2459585

Antenna 111: 2459584

Antenna 111: 2459583

Antenna 111: 2459582

Antenna 111: 2459581

Antenna 111: 2459580

Antenna 111: 2459579

Antenna 111: 2459578

Antenna 111: 2459577

Antenna 111: 2459576

Antenna 111: 2459575

Antenna 111: 2459574

Antenna 111: 2459573

Antenna 111: 2459572

Antenna 111: 2459571

Antenna 111: 2459570

Antenna 111: 2459569

Antenna 111: 2459566

Antenna 111: 2459565

Antenna 111: 2459564

Antenna 111: 2459563

Antenna 111: 2459562

Antenna 111: 2459561

Antenna 111: 2459560

Antenna 111: 2459559

Antenna 111: 2459558

Antenna 111: 2459556

Antenna 111: 2459552

Antenna 111: 2459551

Antenna 111: 2459549

Antenna 111: 2459542

Antenna 111: 2459541

Antenna 111: 2459540

Antenna 111: 2459536

Antenna 111: 2459535

Antenna 111: 2459534

Antenna 111: 2459533

Antenna 111: 2459532

Antenna 111: 2459530

Antenna 111: 2459527

Antenna 111: 2459524

Antenna 111: 2459523

Antenna 111: 2459522

Antenna 111: 2459513

Antenna 111: 2459508

Antenna 111: 2459506

Antenna 111: 2459505

Antenna 111: 2459503

Antenna 111: 2459501

Antenna 111: 2459500

Antenna 111: 2459499

Antenna 111: 2459498

Antenna 111: 2459497

Antenna 111: 2459496

Antenna 111: 2459495

Antenna 111: 2459494

Antenna 111: 2459492

Antenna 111: 2459491

Antenna 111: 2459490

Antenna 111: 2459489

Antenna 111: 2459488

Load antenna metric spectra and waterfalls from `auto_metrics` notebooks.¶